LiteMCP

A TypeScript framework for building MCP (Model Context Protocol) servers elegantly

Deprecate notice:

Since the official SDK already offers a high-level API similar to this project, this project will no longer be maintained.

If you like the CLI commands in this project, you can use them independently: https://github.com/wong2/mcp-cli

Features

• Simple Tool, Resource, Prompt definition
• Full TypeScript support
• Built-in logging
• Built-in error handling
• Built-in CLI for testing and debugging
• Built-in support for SSE transport

Installation

npm install litemcp zod

Quickstart

import { LiteMCP } from "litemcp";
import { z } from "zod";

const server = new LiteMCP("demo", "1.0.0");

server.addTool({
  name: "add",
  description: "Add two numbers",
  parameters: z.object({
    a: z.number(),
    b: z.number(),
  }),
  execute: async (args) => {
    return args.a + args.b;
  },
});

server.addResource({
  uri: "file:///logs/app.log",
  name: "Application Logs",
  mimeType: "text/plain",
  async load() {
    return {
      text: "Example log content",
    };
  },
});

server.start();

You can test the server in terminal with:

npx litemcp dev server.js

Core Concepts

Tools

Tools in MCP allow servers to expose executable functions that can be invoked by clients and used by LLMs to perform actions.

server.addTool({
  name: "fetch",
  description: "Fetch the content of a url",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    const content = await fetchWebpageContent(args.url);
    return content;
  },
});

Resources

Resources represent any kind of data that an MCP server wants to make available to clients. This can include:

• File contents
• Screenshots and images
• Log files
• And more

Each resource is identified by a unique URI and can contain either text or binary data.

server.addResource({
  uri: "file:///logs/app.log",
  name: "Application Logs",
  mimeType: "text/plain",
  async load() {
    return {
      text: await readLogFile(),
    };
  },
});

You can also return binary contents in load:

async load() {
  return {
    blob: 'base64-encoded-data'
  }
}

Prompts

Prompts enable servers to define reusable prompt templates and workflows that clients can easily surface to users and LLMs. They provide a powerful way to standardize and share common LLM interactions.

server.addPrompt({
  name: "git-commit",
  description: "Generate a Git commit message",
  arguments: [
    {
      name: "changes",
      description: "Git diff or description of changes",
      required: true,
    },
  ],
  load: async (args) => {
    return `Generate a concise but descriptive commit message for these changes:\n\n${args.changes}`;
  },
});

Logging

You can send log messages to the client with server.logger

server.addTool({
  name: "download",
  description: "Download a file from a url",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    server.logger.info("Downloading file", { url: args.url });
    // ...
    server.logger.info("Downloaded file", { url: args.url });
    return response;
  },
});

The logger object has the following methods: